f policy to shift the distribution of relative costs
faced by investors in the low-carbon options downward relative to those of higher carbon
options (see Part IV).
42
Note different time periods for different technologies.
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Costs, constraints and energy systems in the longer term
Moving to the longer term highlights the dangers of thinking in terms of individual technologies
instead of energy systems. Most technologies can be expected to progress further and see
unit costs reduced. But all will run into limitations that can be addressed only by
developments elsewhere in the energy system. For example:
•
•
•
•
•
•
•
Energy Storage. With the exception of biofuels, and hydrogen and batteries using low
carbon energy sources, all the low carbon technologies are concerned with the
instantaneous generation of electricity or heat. A major R&D effort on energy storage
and storage systems will be crucial for the achievement of a low-carbon energy
system. This is important for progress in transport, and for expanding the use of low-
carbon technologies, for reasons discussed below.
Decarbonising transport. The transport sector is still likely to remain oil-based for
several decades, and efficiency gains will be important for keeping emissions down.
Increasing use of biofuels will also be important. In the long term, decarbonising
transport will also depend on progress in decarbonising electricity generation and on
developments in hydrogen production. The main technological options currently being
considered for decarbonising transport (other than the contributions of biofuels and
efficiency) are hydrogen and battery-electric vehicles. Much will depend on transport
systems too, including road pricing, intelligent infrastructure, public transport and
urban design.
Nuclear power and base-load electricity generation. A nuclear power plant is
cheapest to operate continuously as base-load generation is expensive to shut down.
There are possibilities of ‘load following’ from nuclear power, but this will reduce
capacity utilisation and raise costs. Most of the load following (where output of the
power plant is varied to meet the changes in the load) will be provided by fossil-fuel
plant in the absence of investments in energy-storage systems. In addition, of course,
there are issues of waste disposal and proliferation to be addressed
Intermittent renewables. Renewables such as solar power and wind power only
generate electricity when the natural resource is available. This leads to
unpredictable and intermittent supply, creating a need for back-up generation. The
cost estimates presented here allow for investment in and the fuel used in doing this,
but, for high levels of market penetration, more efficient storage systems will be
needed.
Bioenergy from crops. Biomass can yield carbon savings in the transport, power
generation, industry and building sectors. However exploitation of conventional
biomass on a large scale could lead to problems of competition with agriculture for
land and water resources, depending on crop practices and policies. This is
discussed in Box 9.6.
The availability and long-term integrity of sites for carbon capture and storage. This
may set limits to the long-term contribution of CCS to a low-carbon economy,
depending on whether alternative ways of storing carbon are discovered in time. It
nevertheless remains an important option given the continued use of cheap fossil
fuels, particularly coal, over the coming decades
Electricity and gas infrastructure. Infrastructure services and their management would
also change fundamentally with the emergence of small-scale decentralised
generation and CHP, and with hydrogen as an energy-carrying and storage medium
for the transport and heat markets. There will also be new opportunities for demand
management through new metering and information and control technologies.
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Box 9.5
PART III: The Economics of Stabilisation
Biomass: emission saving potential and costs
Biomass, the use of crops to produce energy for use in the power generation, transport,
industry and buildings sectors, could yield significant emission savings in the transport, power
and industry sectors. When biomass is grown, it absorbs carbon from the atmosphere during
the photosynthesis process; when the crop is burnt, the carbon is released again. Biomass is
not a zero carbon technology because of the emissions from agriculture and the energy used
in conversion. For example, when used in transport, emissions savings from biofuel vary from
10-90% compared to petrol depending on the source of biofuel and production technique
used.
Biomass crops include starch and sugar crops such as maize and sugar cane, and oil crops
such as sunflower, rapeseed and palm oil. These biocrops are often referred to as first
generation biomass because the technologies for converting them into energy are well
developed. The highest yielding biocrops tend to be water-intensive and require good quality
land, but some other biocrops can be grown on lower quality land with little water.
Research is now focusing on finding ways of converting lignocellulosic materials (such as
trees, grasses and waste materials) into energy (so-called second generation technology).
The technical potential of biomass could be very substantial. On optimistic assumptions, the
total primary bioenergy potential could reach 4,800-12,000 Mtoe by 205043 (compared with
anticipated energy demand under BAU conditions of 22,000 Mtoe in 2050). Half of the
primary biomass would come from dedicated cropland and half would be lignocellulosic
biomass (residues and waste converted into energy). 125-150 million ha would be required
for biomass crops (10% of all arable land worldwide, roughly the size of France and Spain
together). However this analysis does not take into account the potentially significant impacts
on local environment, water and land resources, discussed in Section 12.6. The extent to
which biomass can be produced sustainably and cost effectively will depend on developments
in lignocellulosic technology and to what extent marginal and low-quality land is used for
growing crops.
The economically viable potential for biomass is somewhat smaller, and has been estimated
at up to 2,600 Mtoe, almost a tripling of current biomass use. According to the IEA, this would
result in an emission reduction of 2 to 3 GtCO2e/year on baseline levels by 2050 at $25/tCO2
(though the actual estimate can vary widely around this depending on oil prices). If it is
assumed that one-third of biomass were used for transport fuels by 2050, for example, it
could meet 10% of road transport fuel demand, compared with 1% now. This could grow to
20% under more optimistic assumptions. Biomass costs vary both by crop and by country;
current production costs are lowest in parts of Southern and Central Africa and Latin America.
This analysis excludes the possible emission savings from biogas (methane and CO2
collected from decomposing manure). This technology is discussed in Box 17.7.
These limitations mean that all technologies will run into increasing marginal cost as their
uptake expands, which will offset to some extent the likely reductions in cost as developments
in the technology occur. Some of the constraints might be removed – research is ongoing, for
example, on storing carbon in solid form (see Box 9.2). On the other hand, economies of
scale and induced innovation will serve to bring down costs. Overall, a phased use of
technologies across the board is likely to limit the cost burden of mitigating and sequestering
GHGs.
In the current and next generation of investments over the next 20 years, the costs of climate
change mitigation will probably be low, as some of the more familiar and easier options are
exploited first. But as the scale of mitigation activities expands, at some point the problems
posed by storage and the need to develop new systems and infrastructures must be
43
All the emission saving and cost estimates in this box come from IEA analysis. IEA (2006) and IEA (in press).
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overcome, particularly to meet the needs of transport. This is expected to raise costs (see
below).
When looking forward over a period of several decades, however, there is also significant
scope for surprises and breakthroughs in technology. This is one of the reasons why it is
recommended that R&D and demonstration efforts are increased, both nationally and
internationally (see discussion in Chapters 16 and 24). Such surprises may take the form of
discoveries and innovations not currently factored into mainstream engineering analysis of
energy futures44.
The conclusion to be drawn from the analysis of the costs and risks associated with
developing the various technologies, from the uncertainties as to their rates of development,
and from the known limitations of each, is that no single technology, or even a small subset of
technologies, can shoulder the task of climate-change mitigation alone. If carbon emissions
are to be reduced on the scale shown to be necessary for stabilisation in Chapter 8, then
policies must encourage the development of a portfolio of options; this will act both to reduce
risks and improve the chances of success. Chapter 16 of this Review discusses how this can
be done.
9.8
A technology-based approach to costing mitigation of fossil fuel emissions
This section presents the results of calculations undertaken for this review by Dennis
Anderson45. It illustrates how fossil-fuel (energy) emissions could be cut from 24 GtCO2e/year
in 2002 to 18 GtCO2e/year in 2050 and how much this would cost. Together with the non-
fossil fuel savings outlined in Table 9.1, this would be consistent with a 550ppm CO2e
stabilisation trajectory in 2050 (outlined in Chapter 8).
A key advantage of this exercise is that it is data-driven, transparent, and easy to understand.
It builds on the analysis of options in the preceding section. It illustrates one approach and
establishes a benchmark. This will lead to an upward bias in the estimated costs, as there are
many options, some of which will appear along the way with appropriate R&D, which will be
cheaper. Like any such exercise, however, it depends on its assumptions. An independent
technology-based study has recently been carried out by the IEA (see Section 9.9), which
comes up with rather lower cost estimates. The next chapter reviews studies based on an
economy-wide approach that attempt to incorporate some economic responses to policy
instruments. These are broadly consistent with the results presented here.
The exercise here assumes that energy-related emissions at first rise and are then reduced to
18 GtCO2/year through a combination of improvements in energy efficiency and switching to
less emission-intensive technologies. This calculation looks only at fossil fuel related CO2
emissions, and excludes possible knock-on effects on non-fossil fuel emissions. The precise
approach used and assumptions made are detailed in the full paper46.
Figure 9.3 presents the estimated BAU47 energy-related CO2 emissions over the period to
2075 and the abatement trajectory associated with reducing emissions to reach current levels
by 2050. The abatement trajectory demonstrates a peak in emissions at 29 GtCO2/year in
2025 before falling back to 18 GtCO2/year in 2050, and falling further to reach 7 GtCO2/year
in 2075.
44
Examples might be polymer-based PVs, with prospects for ‘reel-to-reel’ or batch processing; the generation of
hydrogen directly from the action of sunlight on water in the presence of a catalyst (photo-electrolysis); novel
methods and materials for hydrogen storage; small and large-scale energy storage devices more generally, including
one known as the regenerable fuel cell; nuclear fusion; and new technologies and practices for improving energy
efficiency. In addition, the technologies currently under development will also offer scope for ‘learning-by-doing’ and
scale economies in manufacture and use.
45
formerly the Senior Energy Adviser and an economist at the World Bank, Chief Economist of Shell and an engineer in
the electricity supply industry.
46
the Energy Sector.”
47
slightly greater than the BAU projection of fossil fuel emissions used in Chapter 8 and parts of Chapter 7 (of 58
GtCO2/year in 2050).
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GtCO2
PART III: The Economics of Stabilisation
Figure 9.3 Emissions scenarios
Fossil fuel related emissions: BAU and emission
abatement scenario (GtCO2)
80
70
60
50
40
30
20
10
0
2000
2025
2075
BAU emissions
Abatement scenario
2050
A combination of technologies, together with advances in efficiency, are needed to
meet the stabilisation path.
For each technology, assumptions are made on plausible rates of uptake over time48. It is
assumed, for the purposes of simplification, that as the rate of uptake of individual
technologies is modest, they will not run into significant problems of increasing marginal cost
(as discussed above in Section 9.7). Assumptions are also made on the potential for energy-
efficiency improvements. These assumptions can be used to calculate an average cost of
abatement. Estimates of the additional contribution of energy efficiency and technological
inputs to abatement are shown in Figure 9.4. The implications for sources of electricity and
composition of road transport vehicle fleet are illustrated in the full paper.
Figure 9.4 The distribution of emission savings by technology
Contributions to Carbon Abatement, 2050
Efficiency
CCS
Nuclear
Biofuels
dCHP
Solar
Wind
Hydro
Abatement 43 GtCO2
Contributions to Carbon Abatement 2025
Efficiency
CCS
Nuclear
Biofuels
dCHP
Solar
Wind
Hydro
Abatement 11 GtCO2
An average cost of abatement per tonne of carbon can be constructed by calculating the cost
of each technology (as in Box 9.3) weighted by the assumed take-up, and comparing this with
the emissions reductions achieved by these technologies against fossil-fuel alternatives. This
is shown in Figure 9.5, where upper and lower bounds represent best estimates of 90%
confidence intervals.
48
More detail on the assumptions made can be found in Anderson (2006).
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$/tCO2
PART III: The Economics of Stabilisation
Figure 9.5 Average cost of reducing fossil fuel emissions to 18 GtCO2 in 2050*
Cost of carbon abatement ($/tCO2)
150
100
50
0
-50
2000
2010
2020
2030
2040
2050
-100
*The red lines give uncertainty bounds around the central estimate. These have been calculated using Monte Carlo
analysis. For each technology, the full range of possible costs (typically ± 30% for new technologies, ±20% for
established ones) is specified. Similarly, future oil prices are specified as probability distributions ranging from $20 to
over $80 per barrel, as are gas prices (£2-6/GJ), coal prices and future energy demands (to allow for the uncertain
rate of uptake of energy efficiency). This produces a probability distribution that is the basis for the ranges given.
The costs of carbon abatement are expected to decline by half over the next 20 years,
because of the factors discussed above, and then by a further third by 2050. But the longer-
term estimates of shifting to a low-carbon energy system span a very broad range, as
indicated in the figure, and may even be broader than indicated here. This reflects the
inescapable uncertainties inherent in forecasting over a long time period, as discussed above.
It should be noted that, although average costs may fall, marginal costs are likely to be on a
rising trajectory through time, in line with the social cost of carbon; this is explained in Box
9.6.
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Box 9.6
PART III: The Economics of Stabilisation
The relationship between marginal and average costs over time
It is important not to confuse average costs with marginal costs or the prevailing carbon price.
The carbon price should reflect the social cost of carbon and be rising with time, because of
increased additional damages per unit of GHG at higher concentrations of gases in the
atmosphere (see Chapter 13). Rising prices should encourage abatement projects with
successively higher marginal costs. This does not necessarily mean that the average costs
will rise. Indeed, in this analysis, average costs are assumed to fall, quickly at first and then
tending to level off (Figure 9.5). At any time, marginal costs will tend to be above average
costs as the most costly projects are undertaken last.
At the same time, however, innovation, learning and experience – driven through innovation
policy – will lower the cost of producing any given level of output using any specific
technology. This is shown in the figure below, which traces the costs of a specific technology
through time.
Despite more extensive use of the technology and rising costs on the margin through time
(reflecting the rising carbon price), the average cost of the technology may continue to fall.
The key point to note is that marginal costs might be rising even where average costs are
falling (or at least rising more slowly), as a growing range of technologies are used more and
more intensively.
Illustrative cost per unit of GHG abated for a specific technology
Average
cost
Marginal
cost
Quantity of projects ranked
by increasing cost
$/tCO2e
X
X
‘Innovation’ continues to
lower average cost
X
X
Rising social cost of carbon requires
higher marginal cost projects
X
2005
2025
X
2050
Emission cuts
The global cost of reducing total GHG emissions to three quarters of current levels
(consistent with 550ppm CO2e stabilisation trajectory) is estimated at around $1 trillion
in 2050 or 1% of GDP in that year, with a range of –1.0% to 3.5% depending on the
assumptions made.
Anderson’s central case estimate of the total cost of reducing fossil fuel emissions to around
18 GtCO2e/year (compared to 24 GtCO2/year in 2002) is estimated at $930bn, or less than
1% of GDP in 2050 (see table 9.2). In the analysis by Anderson, this is associated with a
saving of 43 GtCO2 of fossil fuel emissions relative to baseline, at an average abatement cost
of $22/tCO2/year in 2050. However these costs vary according to the underlying
assumptions, so these are explored below.
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Table 9.2
PART III: The Economics of Stabilisation
Annual total costs of reducing fossil fuel emissions to 18 GtCO2 in 2050
2015
61
2025
33
2050
22
Average cost of abatement, $/t CO2
Emissions Abated GtCO2
(relative to emissions in BAU)
Total cost of abatement, $ billion per year:
2.2
134
10.7
349
42.6
930
The sensitivity of the cost estimates to different assumptions is presented in Table 9.349;
costs are shown as a percentage of world product. Over the next 20 years, it is virtually
certain that the costs of providing energy will rise with the transition to low-carbon fuels,
barring shocks in oil and gas supplies. Over the longer term, the estimates are less precise
and, as one would expect, are sensitive to the future prices of fossil fuels, to assumptions as
to energy efficiency, and indeed to the prices of the low-carbon technologies, such as carbon
capture and storage.
Overall, the estimates range from -1.0% (a positive contribution to growth) to around 3.5% of
world product by 2050, and are within the range of a large number of other studies discussed
below in the next chapter. The estimates fan out in precisely the same way as those for the
costs per tonne of carbon abatement shown in Figure 9.5, and for precisely the same
reasons50.
Table 9.3 Sensitivity analysis of global costs of cutting fossil fuel
emissions to 18 GtCO2 in 2050 (costs expressed as % of world GDP) a
2015
0.3
0.4
0.2
0.4
0.2
0.3
0.3
0.3
2025
0.7
0.9
0.2
1.1
0.5
0.8
0.5
0.6
2050
1.0
3.3
-1.0
2.4
0.2
1.9
0.7
1.0
Case
(i) Central case
(ii) Pessimistic technology case
(iii) Optimistic technology case
(iv) Low future oil and gas prices
(v) High future oil and gas prices
(vi) High costs of carbon capture and storage
(vii) A lower rate of growth of energy demand
(viii) A higher rate of growth of energy demand
b
(ix) Including incremental vehicle costs
•
•
Means
Ranges
0.4
0.3-0.5
0.8
0.5-1.1
1.4
-0.6- 3.5
a
The world product in 2005 was approximately $35 trillion (£22 trillion at the PPP rate of $1.6/£). It
is assumed to rise to $110 trillion (£70 trillion) by 2050, a growth rate of 2.5% per year, or 1 ½ -2%
in the OECD countries and 4-4½% in the developing countries.
b
Assuming the incremental costs of a hydrogen fuelled vehicle using an internal combustion
engine are £2,300 in 2025 and $1400 in 2050, and for a hydrogen fuelled fuel cell vehicle £5000 in
2025 declining to £1700 by 2050. (Ranges of ~ ± 30% are taken about these averages for the fuel
cell vehicle.)
Assumptions as to future oil and gas prices and rates of innovation clearly make a large
difference to the estimates. Combinations of a return to low oil and gas prices and low rates of
innovation lead to higher costs, while higher oil and gas prices and rates of innovation point to
possibly beneficial effects on growth (even ignoring the benefits of climate change mitigation).
Another cost, which requires attention, is the incremental cost of hydrogen vehicles (case ix).
Costly investment in hydrogen cars would significantly increase the costs associated with this
element of mitigation. However, in so far as such costs might induce a switch out of mitigation
in the transport sector towards alternatives with lower MACs, these estimates are likely to
overstate the true cost impact on the whole economy.
The fossil fuel emission abatement costs outlined in table 9.2 together with the non-fossil fuel
emission savings presented in Table 9.1 would be sufficient to bring global GHG emissions to
49
50
A full specification of the different cases are set out in the full paper.
Rows (ii) and (iii) provide a rough estimate of the confidence intervals associated with the estimates in row (i).
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around 34 GtCO2e in 2050, which is consistent with a 550ppm CO2e stabilisation trajectory.
The cost of this is estimated at under $1 trillion in 2050 (or 1% of GDP in that year).
In absolute terms, the costs are high, but are within the capacity of policies and industry to
generate the required financial resources. For the economy as a whole, a 1% extra cost
would be like a one-off increase in the price index by one percentage point (with unchanged
nominal income profiles), although the impact will be significantly more for energy-intensive
sectors (see Chapter 11). Economies have in the past dealt with much more rapid changes in
relative prices and shocks from exchange-rate changes of much larger magnitude.
9.9
Other technology-based studies on cost
Other modellers have also taken a technology-based approach to looking at emissions
reductions and costs. The IEA, in particular, have done detailed work based on their global
energy models on the technological and economic feasibility of cutting emissions below
business as usual, while also meeting other energy-policy goals.
The recent Energy Technology Perspectives report (2006) looks at a number of scenarios for
reducing energy-related emissions from baseline levels by 2050. Scenarios vary in their
assumptions about factors such as rates of efficiency improvements in various technologies.
Box 9.7 sets out the scenarios in the report, and compares this with work by the IPCC, as well
as the technology-based estimates by Anderson set out in this chapter.
These studies make different assumptions about the quantity of abatement achieved, and the
exact mix of technologies and efficiency measures used to achieve this. But all agree on
some basic points. These are that energy efficiency will make up a very significant proportion
of the total; that a portfolio of low-carbon technologies will be needed; and that CCS will be
particularly important, given the continued use in fossil fuels.
The report also looks at the additional costs for the power-generation sector of achieving
emissions cuts. It finds that in the main alternative policy scenario (‘ACT MAP’), which brings
energy-related emissions down to near current levels by 2050, additional investments of $7.9
trillion would be needed over the next 45 years in low-carbon power technologies, compared
with the baseline scenario. However, there would be $4.5 trillion less spent on fossil-fuel
power plants, in part because of lower electricity demand due to energy-efficiency
improvements. In addition, there would be significant savings in transmission and distribution
costs, and fuel costs; taking these into account brings the total net cost to only $100bn over
45 years.
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Power
Manufacturing
Transport
Buid l n i gs
Box 9.7
PART III: The Economics of Stabilisation
Sources of fossil fuel related emission savings in 2050
IPCC
IEA ‘ACT MAP’
IEA other scenarios
Dennis Anderson
By sector By
technology
31.1
By sector
12.7
GtCO2e
in 2020
Low Low
nuclear renewables No CCS
28.3
GtCO2e
Low
efficiency TECH Plus
26.8
GtCO2e
31.3
GtCO2e GtCO2e
32.1 GtCO2e
Sectors:
Power
Manufacturing &construction
Transport
Buildings
Technologies:
Energy efficiency
CCS
Nuclear
37.4
GtCO2e
Renewables
Fuel mix in buildings & industry
Hydrogen andfuel cells
42.6
GtCO2e
dCHP
The bars in the diagram above show the composition of emissions reductions achieved in
different models. The IPCC work relates to emissions savings in 2020, while the others relate to
emissions savings in 2050. Separately, the IPCC have also estimated plausible emissions
savings from non-energy sectors (discussed in Section 9.4).
The IPCC reviewed studies on the extent to which emissions could be cut in the power,
manufacturing and construction, transport and buildings sectors. They find that for a cost of less
than $25/tCO2e, emissions could be cut by 10.8 – 14.7 GtCO2e in 2020. The savings presented
in the diagram are around the mid-point of this range.
The IEA Energy Technology Perspectives report sets out a range of scenarios for reducing
energy-related CO2 emissions by 2050, based on a marginal abatement cost of $25/tCO2 in
2050, and investment in research and development of new technologies. The ‘ACT MAP’
scenario is the central scenario; the others make different assumptions on, for instance, the
success of CCS technology and the ability to improve energy efficiency. Total emission savings
range from 27 to 37 GtCO2/year. In all scenarios, the IEA find that the CO2 intensity of power
generation is half current levels by 2050. However there is much less progress in the transport
sector in all scenarios apart from TECH PLUS because further abatement from transport is too
expensive. To achieve further emission cuts beyond 2050, transport would have to be
decarbonised.
The forthcoming World Energy Outlook (2006) depicts an Alternative Policy Scenario that
shows how the global energy market could evolve if countries were to adopt all of the policies
they are currently considering related to energy security and energy-related CO2 emissions.
This Alternative Policy Scenario cuts fossil fuel emissions by more than 6 GtCO2/year against
the Reference Scenario by 2030, and finds that there is little difference in the investment
requirements51. The World Energy Outlook (2006) also looks at a more radical path that
would bring energy-related CO2 emissions back to current levels by 2030, through more
aggressive action on energy efficiency and transport and energy technologies, including the
use of second generation biofuels and carbon capture and storage.
51
The alternative policy scenario entails more investment in energy efficient infrastructure, but less investment in
energy production and distribution. These effects broadly cancel one another out so investment requirements are
about the same as in the reference case.
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9.10 Conclusion
The technology-based analysis discussed in this chapter identifies one set of ways in which
total GHG emissions could be reduced to three-quarters of current levels by 2050 (consistent
with a 550ppm CO2e stabilisation trajectory). The costs of doing so amount to under $1 trillion
in 2050, which is relatively modest in relation to the level and expansion of economic output
over the next 50 years, which in any scenario of economic success is likely to be over one
hundred times this amount. They equate to around 1 ± 2½ % of annual GDP – with the IEA
analysis suggesting that the costs could be close to zero. As discussed in the next chapter,
this finding is broadly consistent with macroeconomic modelling exercises. Chapter 10 also
looks at the possible cost implications of aiming for more restrictive stabilisation targets such
as 450ppm CO2e.
This resource-cost analysis suggests that a globally rational world should be able to tackle
climate change at low cost. However, the more imperfect, less rational, and less global policy
is, the more expensive it will be. This will also be examined further in the next chapter.
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References
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non-fossil fuel sources. The IPCC Working Group III Third Assessment Report (TAR,
published in 2001) is the best source of non-fossil fuel emission savings, while work
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deforestation. IPCC has also produced estimates of fossil fuel related emission savings
(2001). IPCC emission saving estimates are expected to be updated in the Fourth
Assessment Report (to be published 2007). The International Energy Agency has produced a
series of publications on how to cut fossil fuel emissions cost effectively; their most up to date
estimates of aggregate sector-wide results are presented in the Energy Technology
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Intergovernmental Panel on Climate Change (2000): 'Land-use, land-use change and
forestry', Special Report of the Intergovernmental Panel on Climate Change [Watson RT,
Noble IR, Bolin B et al. (eds.)], Cambridge: Cambridge University Press.
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Intergovernmental Panel on Climate Change (2001): Climate Change 2001: 'Mitigation'.
Contribution of Working Group III to the Third Assessment Report of the Intergovernmental
Panel on Climate Change [Metz B, Davidson O, Swart R and Pan J (eds.)], Cambridge:
Cambridge University Press.
Intergovernmental Panel on Climate Change (2005): “‘IPCC Special Report on Carbon
Capture and Storage”, Cambridge: Cambridge University Press, November, available from
http://www.ipcc.ch/activity/ccsspm.pdf
Read, P. (2006): ‘Carbon Cycle Management with Biotic Fixation and Long-term Sinks’, in
Avoiding Dangerous Climate Change, H.J. Schellnhuber et al. (eds.), Cambridge: Cambridge
University Press, pp. 373 – 378.
Sachs, J. and K. Lackner (2005): 'A robust strategy for sustainable energy,' Brookings Papers
on Economic Activity, Issue 2, Washington, D.C: The Brookings Institution.
Sathaye, J., W. Makundi, L. Dale and P. Chan (2005 in press): 'GHG mitigation potential,
costs and benefits in global forests: a dynamic partial equilibrium approach'. Energy Journal.
Smith, P., D. Martino, Z. Cai, et al. (2006 in press): 'Greenhouse-gas mitigation in agriculture',
Philosophical Transactions of the Royal Society, B.
Sohngen B and R. Mendelsohn (2003): 'An optimal control model of forest carbon
sequestration', American Journal of Agricultural Economics 85 (2): 448-457, doi:
10.1111/1467-8276.00133
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10 Macroeconomic Models of Costs
Key Messages
Broader behavioural modelling exercises suggest a wide range of costs of
climate-change mitigation and abatement, mostly lying in the range –2 to +5%
of annual GDP by 2050 for a variety of stabilisation paths. These capture a range
of factors, including the shift away from carbon-intensive goods and services
throughout economies as carbon prices rise, but differ widely in their assumptions
about technologies and costs.
Overall, the expected annual cost of achieving emissions reductions,
consistent with an emissions trajectory leading to stabilisation at around 500-
550ppm CO2e, is likely to be around 1% of GDP by 2050, with a range of +/- 3%,
reflecting uncertainties over the scale of mitigation required, the pace of technological
innovation and the degree of policy flexibility.
Costs are likely to rise significantly as mitigation efforts become more
ambitious or sudden, suggesting that efforts to reduce emissions rapidly are
likely to be very costly.
The models arriving at the higher cost estimates for a given stabilisation path
make assumptions about technological progress that are pessimistic by
historical standards and improbable given the cost reductions in low-emissions
technologies likely to take place as their use is scaled up.
Flexibility over the sector, technology, location, timing and type of emissions
reductions is important in keeping costs down. By focusing mainly on energy and
mainly on CO2, many of the model exercises overlook some low-cost abatement
opportunities and are likely to over-estimate costs. Spreading the mitigation effort
widely across sectors and countries will help to ensure that emissions are reduced
where is it cheapest to do so, making policy cost-effective.
While cost estimates in these ranges are not trivial, they are also not high
enough seriously to compromise the world’s future standard of living – unlike
climate change itself, which, if left unchecked, could pose much greater threats
to growth (see Chapter 6). An annual cost rising to 1% of GDP by 2050 poses little
threat to standards of living, given that economic output in the OECD countries is
likely to rise in real terms by over 200% by then, and in developing regions as a
whole by 400% or more.
How far costs are kept down will depend on the design and application of
policy regimes in allowing for ‘what’, ‘where’ and ‘when’ flexibility in seeking low-
cost approaches. Action will be required to bring forward low-GHG technologies,
while giving the private sector a clear signal of the long-term policy environment (see
Part IV).
Well-formulated policies with global reach and flexibility across sectors will
allow strong economic growth to be sustained in both developed and
developing countries, while making deep cuts in emissions.
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10.1 Introduction
The previous chapter calculated the price impact of increasing fossil-fuel costs on the
economy and then developed a detailed technology-based estimation approach, in which the
costs of a full range of low GHG technologies were compared with fossil fuels for a path with
strong carbon emissions abatement. A low-carbon economy with manageable costs is
possible, but will require a portfolio of technologies to be developed. Overall, the economy-
wide costs were found to be around 1% of GDP, though there remains a wide range reflecting
uncertainty over future innovation rates and future fossil-fuel extraction costs and prices.
The focus of this chapter is a comparison of more detailed behavioural modelling exercises,
drawing on a comparative analysis of international modelling studies. Different models have
been tailored to tackle a range of different questions in estimating the total global costs of
moving to a low-GHG economy. Section 10.2 highlights the results from these key models.
The models impose a variety of assumptions, which are identified in section 10.3 and reflect
uncertainty about the real world and differences of view about the appropriate model structure
and, in turn, yield a range of costs estimates. The section investigates the degree to which
specific model structures and characteristics affect cost estimates, in order to draw
conclusions about which estimates are the most plausible and what factors in the real world
are likely to influence them. Section 10.4 puts these estimated costs into a global perspective.
There are also important questions about how these costs will be distributed, winners and
losers, and the implications of countries moving at different speeds. These are examined
further in Chapter 11.
The inter-model comparison reaffirms the conclusion that climate-change mitigation is
technically and economically feasible with mid-century costs most likely to be around
1% of GDP, +/- 3%.
Nevertheless, the full range of cost estimates in the broader studies is even wider. This
reflects the greater number of uncertainties in the more detailed studies, not only over future
costs and the treatment of innovation, but also over the behaviour of producers and
consumers and the degree of policy flexibility across the globe. Any models that attempt to
replicate consumer and producer behaviours over decades must be highly speculative.
Particular aspects can drive particular results especially if they are ‘run forward’ into the
distant future. Such are the difficulties of analysing issues that affect millions of people over
long time horizons. However, such modelling exercises are essential, and the presence of
such a broad and growing range of studies makes it possible to draw judgements on what are
the key assumptions.
10.2 Costs of emissions-saving measures: results from other models
A broader assessment of mitigation costs requires a thorough modelling of consumer
and producer behaviour, as well as the cost and choice of low-GHG technologies.
There have been a number of modelling exercises that attempt to determine equilibrium
allocations of energy and non-energy emissions, costs and prices (including carbon prices),
consistent with changing behaviour by firms and households. The cost estimates that emerge
from these models depend on the assumptions that drive key relationships, such as the
assumed ease with which consumers and producers can substitute into low-GHG activities,
the degree of foresight in making investment decisions and the role of technology in the
evolution of costs.
To estimate how costs can be kept as low as possible, models should cover a broad
range of sectors and gases, as mitigation can take many forms, including land-use and
industrial-process emissions.
Most models, however, are restricted to estimating the cost of altered fossil-fuel combustion
applied mostly to carbon, as this reduces model complexity. Although fossil-fuel combustion
accounts for more than three-quarters of developed economies’ carbon emissions, this
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simplifying assumption will tend to over-estimate costs, as many low-cost mitigation
opportunities in other sectors are left out (for example, energy efficiency, non-CO2 emissions
mitigation in general, and reduced emissions from deforestation; see Chapter 9). Some of the
most up-to-date and extensive comparisons surveyed in this section include:
•
•
•
•
•
•
•
Stanford University’s Energy Modelling Forum (EMF);
the meta-analysis study by Fischer and Morgenstern (Resources For the Future
(2005));
the International Energy Agency accelerated technology scenarios;
the IPCC survey of modelling results;
the Innovation Modelling Comparison Project (IMCP);
the Meta-Analysis of IMCP model projections by Barker et al (2006);
the draft US CCSP Synthesis and Assessment of “Scenarios of Greenhouse-Gas
Emissions and Atmospheric Concentrations and Review of Integrated Scenario
Development and Application” (June 2006).
The wide range of model results reflects the design of the models and their choice of
assumptions, which itself reflects the uncertainties and differing approaches inherent
in projecting the future.
Figure 10.1 uses Barker’s combined three-model dataset to show the reduction in annual CO2
emissions from the baseline and the associated changes in world GDP. Although most of the
model estimates for 2050 are clustered in the –2 to 5% of GDP loss in the final-year cost
range, these costs depend on a range of assumptions. The full range of estimates drawn from
a variety of stabilisation paths and years extends from –4% of GDP (that is, net gains) to
+15% of GDP costs. A notable feature, examined in more detail below, is the greater-than-
proportionate increase in costs to any rise in the amount of mitigation.
This variation in cost estimates is driven by a diversity of characteristics in individual models.
To take two examples, the AIM model shows a marked rise in costs towards 2100, reflecting
the use of only one option – energy conservation – being induced by climate policy, so that
costs rise substantially as this option becomes exhausted. At the opposite extreme, the
E3MG global econometric model assumes market failures due to increasing returns and
unemployed resources in the base case. This means that additional energy-sector
investment, and associated innovation driven by stabilisation constraints, act to increase
world GDP. The fact that there is such a broad range of studies and assumptions is welcome,
making it possible to use meta-analysis1 to determine what factors drive the results.
1
In statistics, a meta-analysis combines the results of several studies that tackle a set of related research
hypotheses. In order to overcome the problem of reduced statistical power in individual studies with small sample
sizes, analysing the results from a group of studies can allow more accurate data analysis.
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Global andUSGWP
differencefrombase (%)
Figure 10.1
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Scatter plot of model cost projections
Costs of CO2 emissions reductions as a fraction of GDP against level of reduction
10
-100
20
CO2 difference from base (%)
IMCP dataset
post-SRES dataset
WRI dataset (USA only)
Source: Barker et al. (2006). Note: GWP should read GDP.
Model comparison exercises help to identify the reasons why the results vary.
To make sense of the growing range of estimates generated, model comparison exercises
have attempted to synthesise the main findings of these models. This has helped to make
more transparent the differences between the assumptions in different models. A meta-
analysis of leading model simulations, undertaken for the Stern Review by Terry Barker2,
shows that some of the higher cost estimates come from models with limited substitution
opportunities, little technological learning, and limited flexibility about when and where to cut
emissions3.
The meta-analysis work essentially treats the output of each model as data, and then
quantifies the importance of parameters and assumptions common to the various models in
generating results. The analysis generates an overarching model, based on estimates of the
impacts of individual model characteristics. This can be used to predict costs as a percentage
of world GDP in any year, for any given mitigation strategy. Table 10.1 shows estimated costs
in 2030 for stabilisation at 450ppm CO2. This corresponds with approximately 500-550ppm
CO2e, assuming adjustments in the emissions of other gases such that, at stabilisation, 10-
20% of total CO2e will be composed of non-CO2 gases (see Chapter 8).
A feature of the model is that it can effectively switch on or off the factors identified as being
statistically and economically significant in cutting costs. For example, the ‘worst case’
assumption assumes that all the identified cost-cutting factors are switched off – in this case,
costs total 3.4% of GDP. At the other extreme, the ‘best case’ projection assumes all the
identified cost-cutting factors are active, in which case mitigation yields net benefits to the
world economy to the tune of 3.9% of GDP. (Table 10.1 lists the individual estimated
contributions to costs from the identified assumptions – a positive percentage point
contribution represents the average reduction in costs when the parameter is ‘switched on’).
2
Terry Barker is the Director of the Cambridge Centre for Climate Change Mitigation Research (4CMR), Department
of Land Economy, University of Cambridge, Leader of the Tyndall Centre’s research programme on Integrated
Assessment Modelling and Chairman of Cambridge Econometrics. He is a Coordinating Lead Author in the IPCC’s
Fourth Assessment Report, due 2007, for the chapter covering mitigation from a cross-sectoral perspective.
3
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Table 10.1 Meta-analysis estimates, contributions to cost reduction
Average impact of model assumptions on world GDP in 2030 for stabilisation at
450ppm CO2 (approximately 500-550ppm CO2e)
(% point levels difference from base model run)
Full equation
Worst case assumptions
Active revenue recycling4
CGE model
Induced technology
Non-climate benefit
International mechanisms
‘Backstop’ technology
Climate benefit
Total extra assumptions
Best-case assumptions
-3.4
1.9
1.5
1.3
1.0
0.7
0.6
0.2
7.3
3.9
Source: Barker et al. 2006
It is immediately obvious that no model includes all of these assumptions to the extent
suggested here. This is because in practice, not all the cost-cutting factors are likely to apply
to the extent indicated here, and the impact of each assumption is likely to be exaggerated
(for example the active recycling parameter is based on the data from only one model2).
Nevertheless, the exercise suggests that the inclusion in individual models of induced
technology, averted non-climate-change damages (such as air pollution) and
international emission-trading mechanisms (such as carbon trading and CDM flows),
can limit costs substantially.
The time paths of costs also depend crucially on assumptions contained within the modelling
exercises. A number of models show costs rising as a proportion of output through to the end
of the century, as the rising social cost of carbon requires ever more costly mitigation options
to be utilised. Other models show a peak in costs around mid-century, after which point costs
fall as a proportion of GDP, reflecting cost reductions resulting from increased innovation (see
Section 10.3). In addition, greater disaggregation of regions, sectors and fuel types allow
more opportunities for substitution and hence tend to lower the overall costs of GHG
mitigation, as does the presence of a ‘backstop’ technology5.
10.3 Key assumptions affecting cost estimates
Other model-comparison exercises, including studies broadening the scope to include non-
carbon emissions, draw similar conclusions to the Barker study. A number of key factors
emerge that have a strong influence in determining cost estimates. These explain not only the
different estimates generated by the models, but also some of the uncertainties surrounding
potential costs in the real world. These considerations are central, not only to generating
realistic and plausible cost estimates, but also to formulating policies that might keep costs
4
The parameter can be interpreted as switched 'off' for models where no account is taken of revenues (effectively
only the changes in relative prices are modelled) and 'on' for models where the revenues are recycled in some way.
Unfortunately, the data underpinning this parameter are thin: among the IMCP models, only E3MG models the use of
revenues at all.
5
determined independently of the level of demand. Thus, ‘backstop’ technologies imply lower abatement costs with the
introduction of carbon taxes. The ‘backstop’ price may vary through technical change. For example, wind, solar, tidal
and geothermal resources may serve as ‘backstop’ technologies, whereas nuclear fission is generally not, because of
its reliance on a potentially limited supply of uranium. In practice, very few technologies will be entirely elastic in
supply: even wind farms may run out of sites, and the best spots for catching and transporting electricity from the sun
may be exhausted quickly.
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low for any given mitigation scenario. The overarching conclusion of the model studies is that
costs can be moderated significantly if many options are pursued in parallel and new
technologies are phased in gradually, and if policies designed to induce new technologies
start sooner rather than later. The details will be quantified bellow, but the following key
features are central to determining cost estimates.
Assumed baseline emissions determine the level of ambition.
The cost of stabilising GHG emissions depends on the amount of additional mitigation
required. This is given by the ‘mitigation gap’ between the emissions goal and the 'business
as usual' (BAU) emissions profile projected in the absence of climate-change policies.
Scenarios with larger emissions in the BAU scenario will require greater reductions to reach
specific targets, and will tend to be more costly. Large differences in baseline scenarios
reflect genuine uncertainty about BAU trends, and different projected paths of global
economic development.
The 2004 EMF study found a marked divergence in baseline Annex 1 (rich) country emissions
projections from around 2040. Rich-country emissions begin at around 26GtCO2 at the start
of the century and then rise to a range of 40-50GtCO2 by mid-century. By 2100, the range of
BAU projections fans out dramatically. Some baseline scenarios show emissions dropping
back towards levels at the start of the century while others show emissions rising towards 95
GtCO2; there is an even spread between these extremes. These different paths encompass a
variety of assumptions about energy efficiency, GHG intensity and output growth, as well as
about exogenous technological progress and land-use policies.
Technological change will determine costs through time.
Costs vary substantially between studies, depending on the assumed rate of technological
learning, the number of learning technologies included in the analysis and the time frame
considered6. Many of the higher cost estimates tend to originate from models without a
detailed specification of alternative technological options. The Barker study found that the
inclusion of induced technical change could lower the estimated costs of stabilisation by one
or two percentage points of GDP by 2030 (see table 10.1). All the main studies found that the
availability of a non-GHG ‘backstop’ (see above) lowered predicted costs if the option came
into play. Chapter 16 shows that climate policies are necessary to provide the incentive for
low-GHG technologies. Without a ‘loud, legal and long’ carbon price signal, in addition to
direct support for R&D, the technologies will not emerge with sufficient impact (see Part IV).
How far costs are kept down will depend on the design and application of policy regimes in
allowing for ‘what’, ‘where’ and ‘when’ flexibility in seeking low-cost approaches. Action will be
required to bring forward low-GHG technologies, while giving the private sector a clear signal
of the long-term policy environment (see Part IV).
Abatement costs are lower when there is ‘what’ flexibility: flexibility over how emission
savings are achieved, with a wide choice of sectors and technologies and the inclusion
of non-CO2 emissions.
Flexibility between sectors. It will be cheaper, per tonne of GHG, to cut emissions from
some sectors rather than others because there will be a larger selection of better-developed
technologies in some. For example, the range of emission-saving technologies in the power
generation sector is currently better developed than in the transport sector. However, this
does not mean that the sectors with a lack of technology options do nothing in the meantime.
Indeed, innovation policies will be crucial in bringing forward clean technologies so that they
are ready for introduction in the long term. The potential for cost-effective emission saving is
also likely to be less in those sectors in which low-cost mitigation options have already been
undertaken. Similarly, flexibility to cut emissions from a range of consumption options and
economic sectors is also likely to reduce modelled costs. Models that are restricted to a
6
Grubb et al. (2006). See also Grubler et al. (1999), Nakicenovic (2000), Jaffe et al. (2003) and Köhler (2006)
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narrow range of sectors with inelastic demand, for example, parts of the transport sector, will
tend to estimate very high costs for a given amount of mitigation (see Section 10.2).
Flexibility between technologies. Using a portfolio of technologies is cheaper because
individual technologies are prone to increasing marginal costs of abatement, making it
cheaper to switch to an alternative technology or measure to secure further savings. There is
also a lot of uncertainty about which technologies will turn out to be cheapest so it is best to
keep a range of technology options open. It is impossible to predict accurately which
technologies will experience breakthroughs that cause costs to fall and which will not.
Flexibility between gases. Broadening the scope of mitigation in the cost-modelling
exercises to include non-CO2 gases has the potential to lower the costs by opening up
additional low-cost abatement opportunities. A model comparison by the Energy Modelling
Forum7 has shown that including non-carbon greenhouse gases (NCGGs) in mitigation
analysis can achieve the same climate goal at considerably lower costs than a CO2-only
strategy. The study found that model estimates of costs to attain a given mitigation path fell by
about 30–40% relative to a CO2-only approach, with the largest benefits occurring in the first
decades of the scenario period, with abatement costs on the margin falling by as much as
80%. It is notable that the impacts on costs are very substantial in comparison to the much
smaller contribution of NCGGs to overall emissions, reflecting the low-cost mitigation options
and the increase in flexibility of abatement options from incorporating a multi-gas approach8 9.
However, given that climate change is a product of the stock of greenhouse gases in the
atmosphere, the lifetime of gases in the atmosphere also has to be taken into account (see
Chapter 8). Strategies that focus too much on some of the shorter-lived gases risk locking in
to high future stocks of the longer-lived gases, particularly CO2.
Some countries can cut emissions more cheaply than other countries, so ‘where’
flexibility is important.
Flexibility over the distribution of emission-saving efforts across the globe will also help to
lower abatement costs, because some countries have cheaper abatement options than
others10.
•
•
The natural resource endowments of some countries will make some forms of
emissions abatement cheaper than in other countries. For example, emission
reduction from deforestation will only be possible where there are substantial
deforestation emissions. Brazil is well suited to growing sugar, which can be used to
produce biofuel cheaply, although, to the extent that biofuels can be transported,
other countries are also likely to benefit. Brazil, like many other developing countries,
also has a very good wind resource. In addition, the solar resources of developing
countries are immense, the incident solar energy per m2 being 2-2.5 times greater
than in most of Europe, and it is better distributed throughout the year (see Chapter
9).
Countries that have already largely decarbonised their energy sector are likely
to find further savings there expensive. They will tend to focus on the scope for
emissions cuts elsewhere. Energy-efficiency measures are typically among the
7
8
low cost. The study looked at how the world might meet a stabilisation objective if it selected the least-cost abatement
among energy-related CO2 emissions and non-CO2 emissions (but not land use). Two stabilisation scenarios were
compared (aimed at stabilising emissions to 650ppm CO2e): one in which only energy-related CO2 emissions could
be cut; and another in which energy-related CO2 emissions and non-CO2 gases could be reduced. In the ‘energy-
related CO2 emissions only’ scenario, CO2 emissions fall by 75% on baseline levels in 2100. Some non-CO2 gases
also fall as an indirect consequence. In the multi-gas scenario, CO2 emissions fall by a lesser extent (67% by 2100)
and there are significant cuts in the non-CO2 gases (CH4 falling by 52%, N2O by 38%, F-gases by 73%). CO2
remains the major contributor to emission savings, because it represents the biggest share in GHG emissions.
9
10
policy should be designed to achieve emissions reductions, while Chapter 11 examines the possible impacts on
national competitiveness.
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cheapest abatement options, and energy efficiency varies hugely by country. For
example, unit energy and carbon intensity are particularly low in Switzerland
(1.2toe/$GDP and 59tc/$GDP respectively in 2002), reflecting the compositional
structure of output and the use of low-carbon energy production. By contrast, Russia
and Uzbekistan remain very energy- and carbon-intensive (12.5toe/$GDP and
840tc/$GDP respectively for Uzbekistan in 2002), partly reflecting aging capital stock
and price subsidies in the energy market (see, for example, Box 12.3 on gas flaring in
Russia).
It will also be cheaper to pursue emission cuts in countries that are in the
process of making big capital investments. The timing of emission savings will
also differ by country, according to when capital stock is retired and when savings
from longer-term investments such as innovation programmes come to fruition.
Countries such as India and China are expected to increase their capital
infrastructure substantially over coming decades, with China alone accounting for
around 15% of total global energy investment. If they use low-emission technologies,
emission savings can be ‘locked in’ for the lifetime of the asset. It is much cheaper to
build a new piece of capital equipment using low-emission technology than to retro-fit
dirty capital stock.
The Barker study also found that the presence of international mechanisms under the Kyoto
Protocol (which include international emissions trading, joint implementation and the Clean
Development Mechanism) allow for greater flexibility about where cuts are made across the
globe. This has the potential to reduce costs of stabilising atmospheric GHG concentrations at
approximately 500-550ppm CO2e by almost a full percentage point of world GDP1112.
Similarly, Babiker et al. (2001) concluded that limits on ‘where’ flexibility, through the
restriction of trading between sectors of the US economy, can substantially increase costs, by
up to 80% by 2030.
Changes in consumer and producer behaviour through time are uncertain, so ‘when’
flexibility is desirable.
The timing of emission cuts can influence total abatement cost and the policy implications. It
makes good economic sense to reduce emissions at the time at which it is cheapest to do so.
Thus, to the extent that future abatement costs are expected to be lower, the total cost of
abatement can be reduced by delaying emission cuts. However, as Chapter 8 set out, limits
on the ability to cut emissions rapidly, due to the inertia in the global economy, mean that
delays to action can imply very high costs later.
Also, as discussed above, the evolution of energy technologies to date strongly suggests that
there is a relationship between policy effort on innovation and technology cost. Early policy
action on mitigation can reduce the costs of emission-saving technologies (as discussed in
Chapter 15).
Cost-effective planning and substituting activities across time require policy stability, as well
as accurate information and well-functioning capital markets. Models that allow for perfect
foresight together with endogenous investment possibilities tend to show much reduced
costs. Perfect foresight is not an assertion to be taken literally, but it does show the
importance of policy being transparent and predictable, so that people can plan ahead
efficiently.
11
Richels et al (1998) found that international co-operation through trade in emission rights is essential to reduce
mitigation costs of the Kyoto protocol. The magnitude of the savings would depend on several factors including the
number of participating countries and the shape of each country’s marginal abatement cost curve. Weyant and Hill
(1999) assessed the importance of emissions permits and found that they had the potential to reduce OECD costs by
0.1ppt to 0.9ppt by as early as 2010.
12
non-CO2 gas abatement, and a regime that is globally less comprehensive and mimics the present ratification of the
Kyoto Protocol. The study found that, by 2100, the abatement programme that is globally comprehensive, but has
limited coverage of gases (non-CO2only), might be as much as twice as effective at limiting global mean temperature
increases and less expensive than the Kyoto framework.
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The ambition of policy has an impact on estimates of costs.
A common feature of the model projections was the presence of increasing marginal costs to
mitigation. This applies not just to the total mitigation achieved, but also the speed at which it
is brought about. This means that each additional unit reduction of GHG becomes more
expensive as abatement increases in ambition and also in speed. Chapter 13 discusses
findings from model comparisons and shows a non-linear acceleration of costs as more
ambitious stabilisation paths are pursued. The relative absence of energy model results for
stabilisation concentrations below 500ppm CO2e is explained by the fact that carbon-energy
models found very significant costs associated with moving below 450ppm, as the number of
affordable mitigation options was quickly exhausted. Some models were unable to converge
on a solution at such low stabilisation levels, reflecting the absence of mitigation options and
inflexibilities in the diffusion of ‘backstop’ technologies.
In general, model comparisons find that the cost of stabilising emissions at 500-
550ppm CO2e would be around a third of doing so at 450-500ppm CO2e.
The lesson here is to avoid doing too much, too fast, and to pace the flow of mitigation
appropriately. For example great uncertainty remains as to the costs of very deep reductions.
Digging down to emissions reductions of 60-80% or more relative to baseline will require
progress in reducing emissions from industrial processes, aviation, and a number of areas
where it is presently hard to envisage cost-effective approaches. Thus a great deal depends
on assumptions about technological advance (see Chapters 9, 16 and 24). The IMCP studies
of cost impacts to 2050 of aiming for around 500-550ppm CO2e were below 1% of GDP for all
but one model (IMACLIM), but they diverged afterwards. By 2100, some fell while others rose
sharply, reflecting the greater uncertainty about the costs of seeking out successive new
mitigation sources.
Consequently, the average expected cost is likely to remain around 1% of GDP from
mid-century, but the range of uncertainty is likely to grow through time.
Potential co-benefits need to be considered.
The range of possible co-benefits is discussed in detail in Chapter 12. The Barker meta-
analysis found that including co-benefits could reduce estimated mitigation costs by 1% of
GDP. Such models estimate, for example, the monetary value of improved health due to
reduced pollution and the offsetting of allocative efficiency losses through reductions in
distortionary taxation. Pearce (1996) highlighted studies from the UK and Norway showing
benefits of reduced air pollution that offset the costs of carbon dioxide abatement costs by
between 30% and 100%. A more recent review of the literature13 came to similar conclusions,
noting that developing countries would tend to have higher ancillary benefits from GHG
mitigation compared with developed countries, since, in general, they currently incur greater
costs from air pollution.
Analyses carried out under the Clean Air for Europe programme suggest cost savings as high
as 40% of GHG mitigation costs are possible from the co-ordination of climate and air
pollution policies14. Mitigation through land-use reform has implications for social welfare
(including enhanced food security and improved clean-water access), better environmental
services (such as higher water quality and better soil retention), and greater economic welfare
through the impact on output prices and production15. These factors are difficult to measure
with accuracy, but are potentially important and are discussed further in Chapter 12.
13
14
15
OECD et al. 2000
Syri et al. 2001
A difficulty in evaluating the exact benefits of climate polices to air pollution is the different spatial and temporal
scales of the two issues being considered. GHGs are long-lived and hence global in their impact while air pollutants
are shorter-lived and tend to be more regional or local in their impacts.
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Box 10.1
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The relationship between marginal and average carbon cost estimates
It is important to distinguish marginal from average carbon costs. In general, the marginal cost
of carbon mitigation will rise as mitigation becomes more expensive, as low-cost options are
exhausted and diminishing returns to scale are encountered. But the impact on overall costs
to the economy is measured by the average cost of mitigation, which will be lower than those
on the margin.
In some cases, for example, where energy efficiency increases or where induced technology
reduces the costs of mitigation, average costs might not rise and could be zero or negative,
even where costs on the margin are positive and rising. The correlation from plotting carbon
tax against losses in GDP from the IMCP study is only 0.37; a survey for the US Congress by
Lasky (2003) showed that a similar low correlation can be seen from model results on the US
costs of Kyoto (2003, p.92).
Changes in the marginal carbon cost are related, but do not correspond one-for-one, to the
average cost of mitigation. The social cost of carbon will tend to rise as the stock of
atmospheric GHGs, and associated damages, rises. The marginal abatement cost will also
rise, reflecting this, but average abatement costs may fall (see Chapter 9). This explains why
some of the models with a high social cost of carbon, and corresponding high carbon price,
show very low average costs. The high carbon price is assumed to be necessary to induce
benefits from energy efficiency, technological innovation and other co-benefits such as lower
pollution. In some cases, these result in a reduction in average costs that raise GDP above
the baseline when a stabilisation goal is imposed. This also explains why the work by
Anderson (Chapter 9) shows a falling average cost of carbon through time consistent with
rising costs on the margin.
Most models represent incentives to change emissions trajectories in terms of the marginal
carbon price required. This not only changes specific investments according to carbon
content, but also triggers technical change through the various mechanisms considered in the
models, including through various forms of knowledge investment. The IMCP project (Grubb
et al. 2006) charts the evolution of carbon prices required to achieve stabilisation and shows
that they span a wide range, both in absolute terms and in the time profile. For stabilisation at
450ppm (around 500-550ppm CO2e), most models show carbon prices start off low and rise
to US$360/tCO2 +/- 150% by 2030, and are in the range US$180-900/tCO2 by 2050, as the
social cost of carbon increases and more expensive mitigation options need to be
encouraged on the margin in order to meet an abatement goal.
After that, they diverge significantly: some increase sharply as the social cost of carbon
continues to rise. Others level off as the carbon stock and corresponding social cost of carbon
stabilise and a breadth of mitigation options and technologies serve to meet the stabilisation
objective. Rising marginal carbon prices need not mean that GDP impacts grow
proportionately, as new technologies and improved energy efficiency will reduce the
economy's dependence on carbon, narrowing the economic base subject to the higher carbon
taxation.
10.4 Understanding the scale of total global costs
Overall, the model simulations demonstrate that costs depend on the design and application
of policy, the degree of global policy flexibility, and, whether or not governments send the right
signals to markets and get the most efficient mix of investment. If mitigation policy is timed
poorly, or if cheap global mitigation options are overlooked, the costs can be high.
To put these costs into perspective, the estimated effects of even ambitious climate change
policies on economic output are estimated to be small – around 1% or less of national and
world product, averaged across the next 50 to 100 years – provided policy instruments are
applied efficiently and flexibly across a range of options around the globe. This will require
early action to retard growth in the stock of GHGs, identify low-cost opportunities and prevent
locking-in to high GHG infrastructure. The numbers involved in stabilising emissions are
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potentially large in absolute terms – maybe hundreds of billions of dollars annually (1% of
current world GDP equates to approximately $350-400 billion) – but are small in relation to
the level and growth of output.
For example, if mitigation costs 1% of world GDP by 2100, relative to the hypothetical ‘no
climate change’ baseline, this is equivalent to the growth rate of annual GDP over the period
dropping from 2.5% to 2.49%. GDP in 2100 would still be approximately 940% higher than
today, as opposed to 950% higher if there were no climate-change to tackle. Alternatively, one
can think of annual GDP being 1% lower through time, with the same growth rate, after an
initial adjustment. The same level of output is reached around four or five months later than
would be the case in the absence of mitigation costs16.
The illustration of costs above assumes no change in the baseline growth rate relative to the
various mitigation scenarios, that is, it takes no account of climate-change damages. In
practice, by 2100, the impacts of climate change make it likely that the ‘business as usual’
level of world GDP will be lower than the post-mitigation profile (see Chapters 6 and 13).
Hence stabilising at levels around 500-550ppm CO2e need not cost more than a year’s
deferral of economic growth over the century with broad-based, sensible and comprehensive
policies. Once damages are accounted for, mitigation clearly protects growth, while failing to
mitigate does not.
The mitigation costs modelled in this chapter are unlikely to make the same kind of material
difference to household lifestyles and global welfare as those which would arise with the
probable impact of dangerous climate change, in the absence of mitigation (see section II).
The importance of weighing together the costs, benefits and uncertainties through time is
emphasised in Chapter 13.
10.5 Conclusion
This chapter draws on a range of model estimates with a variety of assumptions. A detailed
analysis of the key drivers of costs suggests the estimated effects of ambitious policies to
stabilise atmospheric GHGs on economic output can be kept small, rising to around 1% of
national and world product averaged over the next fifty years.
By 2050, models suggest a plausible range of costs from –2% (net gains) to +5% of GDP,
with this range growing towards the end of the century, because of the uncertainties about the
required amount of mitigation, the pace of technological innovation and the efficiency with
which policy is applied across the globe. Critically, these costs rise sharply as mitigation
becomes more ambitious or sudden.
Whether or not the costs are actually minimised will depend on the design and application of
policy regimes in allowing for ‘what, where and when’ flexibility, and taking action to bring
forward low-GHG technologies while giving the private sector a clear signal of the long-term
policy environment.
These costs, however, will not be evenly distributed. Issues around the likely distribution of
costs are explored in the next chapter. Possible opportunities and benefits arising from
climate-change policy also need to be taken into account in any serious consideration of what
the true costs will be, and of the implications of moving at different speeds. These are
examined further in Chapter 12.
16
See, for example, Azar (2002)
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11 Structural Change and Competitiveness
Key Messages
The costs of mitigation will not be felt uniformly across countries and sectors.
Greenhouse-gas-intensive sectors, and countries, will require the most structural
adjustment, and the timing of action by different countries will affect the balance of costs
and benefits.
If some countries move more quickly than others in implementing carbon reduction
policies, there are concerns that carbon-intensive industries will locate in countries
without such policies in place. A relatively small number of car
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